Laura Bonnett was kind enough to send me a copy of the data that caused the plotting error, since it was an error I had not seen before.
1. The latest version of survival gives a nicer error message: > fit <- coxph(Surv(rem.Remtime, rem.Rcens) ~ all.sex, nearma) > cfit <- cox.zph(fit) > plot(cfit) Error in plot.cox.zph(cfit) : Spline fit is singular, try a smaller degrees of freedom 2. What's the problem? There are 1085 events in the data set (rem.Rcens==1), and of these 502 are tied events on exactly day 365. The plot.cox.zph function tries to fit a smoothing spline to the data to help the eye; the fit gives weight 1 to each death and having this high a proportion of ties creates problems for the underlying regression. 3. > plot(cfit, df=2) Warning messages: 1: In approx(xx, xtime, seq(min(xx), max(xx), length = 17)[2 * (1:8)]) : collapsing to unique 'x' values 2: In approx(xtime, xx, temp) : collapsing to unique 'x' values These warning messages are ignorable. I'll work on making them go away. 4. A shot in the dark -- is perchance the variable rem.Rcens=1 a marker of a censored observation, and the events are 0? (A whole lot of events at 1 year is suspicious, but half censored at one year is believable.) Then the proper coxph code is > fit2 <- coxph(Surv(rem.Remtime, rem.Rcens==0) ~ all.sex, nearma) Terry Therneau ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.